Resource allocation in realistic wireless cognitive radios networks

Cognitive radio networks provide an effective solution for improving spectrum usage for wireless users. In particular, secondary users can now compete with each other to access idle, unused spectrum from licensed primary users in an opportunistic fashion. This is typically done by using cognitive radios to sense the presence of primary users and tuning to unused spectrum bands to boost efficiency. Expectedly, resource allocation is a very crucial concern in such settings, i.e., power and rate control, and various studies have looked at this problem area. However, the existing body of work has mostly considered the interactions between secondary users and has ignored the impact of primary user behaviors. Along these lines, this dissertation addresses this crucial concern and proposes a novel primary-secondary game-theoretic solution which rewards primary users for sharing their spectrum with secondary users. In particular, a key focus is on precisely modeling the performance of realistic channel models with fading. This is of key importance as simple additive white Gaussian noise channels are generally not very realistic and tend to yield overly optimistic results. Hence the proposed solution develops a realistic non-cooperative power control game to optimize transmit power in wireless cognitive radios networks running code division multiple access up-links. This model is then analyzed for fast and slow flat fading channels. Namely, the fading coefficients are modeled using Rayleigh and Rician distributions, and closed-form expressions are derived for the average utility functions. Furthermore, it is also shown that the strategy spaces of the users under realistic conditions must be modified to guarantee the existence of a unique Nash Equilibrium point. Finally, linear pricing is introduced into the average utility functions for both Rayleigh and Rician fast-flat fading channels, i.e., to further improve the proposed models and minimize transmission power for all users. Detailed simulations are then presented to verify the performance of the schemes under the proposed realistic channel models. The results are also compared to those with more basic additive white Gaussian noise channels

Non-cooperative Feedback Rate Control Game for Channel State Information in Wireless Networks

It has been well recognized that channel state information (CSI) feedback is of great importance for dowlink transmissions of closed-loop wireless networks. However, the existing work typically researched the CSI feedback problem for each individual mobile station (MS), and thus, cannot efficiently model the interactions among self-interested mobile users in the network level. To this end, in this paper, we propose an alternative approach to investigate the CSI feedback rate control problem in the analytical setting of a game theoretic framework, in which a multiple-antenna base station (BS) communicates with a number of co-channel MSs through linear precoder. Specifically, we first present a non-cooperative feedback-rate control game (NFC), in which each MS selects the feedback rate to maximize its performance in a distributed way. To improve efficiency from a social optimum point of view, we then introduce pricing, called the non-cooperative feedback-rate control game with price (NFCP). The game utility is defined as the performance gain by CSI feedback minus the price as a linear function of the CSI feedback rate. The existence of the Nash equilibrium of such games is investigated, and two types of feedback protocols (FDMA and CSMA) are studied. Simulation results show that by adjusting the pricing factor, the distributed NFCP game results in close optimal performance compared with that of the centralized scheme.Comment: 26 pages, 10 figures; IEEE Journal on Selected Areas in Communications, special issue on Game Theory in Wireless Communications, 201

Competition in Wireless Systems via Bayesian Interference Games

We study competition between wireless devices with incomplete information about their opponents. We model such interactions as Bayesian interference games. Each wireless device selects a power profile over the entire available bandwidth to maximize its data rate. Such competitive models represent situations in which several wireless devices share spectrum without any central authority or coordinated protocol. In contrast to games where devices have complete information about their opponents, we consider scenarios where the devices are unaware of the interference they cause to other devices. Such games, which are modeled as Bayesian games, can exhibit significantly different equilibria. We first consider a simple scenario of simultaneous move games, where we show that the unique Bayes-Nash equilibrium is where both devices spread their power equally across the entire bandwidth. We then extend this model to a two-tiered spectrum sharing case where users act sequentially. Here one of the devices, called the primary user, is the owner of the spectrum and it selects its power profile first. The second device (called the secondary user) then responds by choosing a power profile to maximize its Shannon capacity. In such sequential move games, we show that there exist equilibria in which the primary user obtains a higher data rate by using only a part of the bandwidth. In a repeated Bayesian interference game, we show the existence of reputation effects: an informed primary user can bluff to prevent spectrum usage by a secondary user who suffers from lack of information about the channel gains. The resulting equilibrium can be highly inefficient, suggesting that competitive spectrum sharing is highly suboptimal.Comment: 30 pages, 3 figure

On the Two-user Multi-carrier Joint Channel Selection and Power Control Game

In this paper, we propose a hierarchical game approach to model the energy efficiency maximization problem where transmitters individually choose their channel assignment and power control. We conduct a thorough analysis of the existence, uniqueness and characterization of the Stackelberg equilibrium. Interestingly, we formally show that a spectrum orthogonalization naturally occurs when users decide sequentially about their transmitting carriers and powers, delivering a binary channel assignment. Both analytical and simulation results are provided for assessing and improving the performances in terms of energy efficiency and spectrum utilization between the simultaneous-move game (with synchronous decision makers), the social welfare (in a centralized manner) and the proposed Stackelberg (hierarchical) game. For the first time, we provide tight closed-form bounds on the spectral efficiency of such a model, including correlation across carriers and users. We show that the spectrum orthogonalization capability induced by the proposed hierarchical game model enables the wireless network to achieve the spectral efficiency improvement while still enjoying a high energy efficiency.Comment: 31 pages, 13 figures, accepted in IEEE Transactions on Communication

SPECTRUM SHARING IN COGNITIVE RADIO NETWORKS WITH QUALITY OF SERVICE AWARENESS

The goal of this thesis is to study performance of cognitive radio networks in terms of total spectrum utilization and throughput of secondary networks under perfect and imperfect sensing for Additive White Gaussian Noise (AWGN) and fading channels. The effect of imperfect sensing was studied by applying non-collaborative and collaborative sensing techniques using energy detecting and square law combining techniques, respectively. Spectrum allocation for heterogeneous networks in cognitive radio networks was discussed and a new sharing algorithm that guarantee Quality of Service (QoS) for different secondary users’ applications was proposed. The throughput degradation of secondary users due to the activities of the primary users was explored by varying the arrival rate of the primary users in a given spectrum band. Computer simulation showed that increasing the primary user’s activity will increase the total spectrum utilization but decreases the secondary users’ throughput simultaneously. The effect of the received Signal to Noise Ratio (SNR) of the primary user on the cognitive radio network performance is studied in which, a high SNR of primary users led to a higher throughput of secondary network in AWGN channels compared to Nakagami fading channels. The effect of applying cooperative sensing is also presented in this thesis. As we increased the number of cooperating sensors, the network throughput increased which proves the advantage of applying cooperative sensing. A spectrum allocation algorithm for heterogeneous network model is developed to study the QoS assurance of secondary users in cognitive radio networks. The system performance of the heterogeneous network was investigated in terms of the total spectrum utilization. It is found that, higher number of secondary users, better channel’s condition and low required QoS of applications would increase the spectrum utilization significantly. vii In this thesis, the proposed allocation algorithm was applied to the heterogeneous cognitive radio model and its performance was compared to the First Come First Served (FCFS) algorithm in both AWGN and fading channels. The proposed algorithm provided a higher average SNR and spectrum utilization than FCFS algorithm and guaranteed the QoS requirement for applications of secondary users. The effect of imperfect sensing on the system performance was investigated, and it was shown that, as the probability of detection increases the total applications’ data rate increases significantly. The proposed algorithm guaranteed the QoS requirement for each application of secondary users. The effect of imperfect sensing on the system performance was investigated, and it was shown that, as the probability of detection increases the total data rate increases significantly

Distributed Game Theoretic Optimization and Management of Multichannel ALOHA Networks

The problem of distributed rate maximization in multi-channel ALOHA networks is considered. First, we study the problem of constrained distributed rate maximization, where user rates are subject to total transmission probability constraints. We propose a best-response algorithm, where each user updates its strategy to increase its rate according to the channel state information and the current channel utilization. We prove the convergence of the algorithm to a Nash equilibrium in both homogeneous and heterogeneous networks using the theory of potential games. The performance of the best-response dynamic is analyzed and compared to a simple transmission scheme, where users transmit over the channel with the highest collision-free utility. Then, we consider the case where users are not restricted by transmission probability constraints. Distributed rate maximization under uncertainty is considered to achieve both efficiency and fairness among users. We propose a distributed scheme where users adjust their transmission probability to maximize their rates according to the current network state, while maintaining the desired load on the channels. We show that our approach plays an important role in achieving the Nash bargaining solution among users. Sequential and parallel algorithms are proposed to achieve the target solution in a distributed manner. The efficiencies of the algorithms are demonstrated through both theoretical and simulation results.Comment: 34 pages, 6 figures, accepted for publication in the IEEE/ACM Transactions on Networking, part of this work was presented at IEEE CAMSAP 201

Transmitter Optimization in Multiuser Wireless Systems with Quality of Service Constraints

In this dissertation, transmitter adaptation for optimal resource allocation in wireless communication systems are investigated. First, a multiple access channel model is considered where many transmitters communicate with a single receiver. This scenario is a basic component of a. wireless network in which multiple users simultaneously access the resources of a wireless service provider. Adaptive algorithms for transmitter optimization to meet Quality-of-Service (QoS) requirements in a distributed manner are studied. Second, an interference channel model is considered where multiple interfering transmitter-receiver pairs co-exist such that a given transmitter communicates with its intended receiver in the presence of interference from other transmitters. This scenario models a wireless network in which several wireless service providers share the spectrum to offer their services by using dynamic spectrum access and cognitive radio (CR) technologies. The primary objective of dynamic spectrum access in the CR approach is to enable use of the frequency band dynamically and opportunistically without creating harmful interference to licensed incumbent users. Specifically, CR users are envisioned to be able to provide high bandwidth and efficient utilization of the spectrum via dynamic spectrum access in heterogeneous networks. In this scenario, a distributed method is investigated for combined precoder and power adaptation of CR transmitters for dynamic spectrum sharing in cognitive radio systems. Finally, the effect of limited feedback for transmitter optimization is analyzed where precoder adaptation uses the quantized version of interference information or the predictive vector quantization for incremental updates. The performance of the transmitter adaptation algorithms is also studied in the context of fading channels